The thesis examination of the doctoral student (Akram Hashim Hameed), majoring in Control Engineering, was conducted at the Control and Systems Engineering Department, the University of Technology. The thesis is entitled: (Advanced Barrier Function Sliding Mode Control and Observer Techniques for Electromechanical Systems with Unmatched Perturbations) The examination was accomplished in Hall no. 9 at 9:00 A.M on Monday 16-9-2024. Then, the student was awarded the Ph.D. degree in Control Engineering. The discussion committee consisted of the following members: 1- Prof. Dr. Safana Mudher Raafat / Chairman 2- Prof. Dr. Imad Qasim Hussein / Member 3- Prof. Dr. Abbas Hussein Issa / Member 4- Asst. Prof. Dr. Ayman Daoud Salman / Member 5- Asst. Prof. Dr. Wissam Esmat Abdel Latif / Member 6- Prof. Dr. Shibli Ahmed Hamid / Member and Supervisor 7- Prof. Dr. Amjad Jalil Hamidi / Member and Supervisor Practically, the Electro-Mechanical systems are dealt with as perturbed systems, either by considering the parametric uncertainty or exerted disturbances. The case of such a perturbed system is the non-vanishing unmatched perturbation. In this thesis, a novel one-instant flux observer that can provide an accurate flux estimation with minimizable ultimate bound estimation error is proposed, mathematically proved, and simulated. The proposed barrier function integral sliding mode (BFISM) observer is tested alongside the relevant observers on the rotor flux observation for the three-phase induction motor. The proposed observer has been compared with the open-loop observer, the nonlinear observer, and the conventional Wallcot-Zak sliding mode (SM) observer. Moreover, backstepping based on a barrier function integral sliding mode controller (BS-BFISMC) has been designed and tested on three electromechanical systems named the IM speed control, DC motor-driven EV speed control, and throttle angle position control of ETV. The proposed controller is compared to relevant controllers where the performance indices of the comparison are the percentage ratio of the RMSE of the tracking error, the perturbation estimation error, and the root mean square input (RMSI) of the control effort.  

 A master’s thesis was discussed in the Department of Control and Systems Engineering by the student (Zeena Mustafa Ali) majoring in (Computer Engineering ) on Thursday, 12, September 2024, at Hall No.9 in the Control and Systems Engineering Department. The research was entitled: "Performance Improvement of Baseband Wireless Communication" The discussion committee consisted of: 1- Asst. Prof. Dr. Fadel Saheb Hassan / Chairman 2- Asst. Prof. Dr. Ali Majeed Muhmood /Member 3- Asst. Prof. Dr. Ahmed Raouf Naser / Member 4- Asst. Prof. Dr. Ikhlas Kadhum Hamza / Member and Supervisor This thesis included the implementation of an internal positioning system for a hybrid network with a deep learning algorithm with higher accuracy, lower cost and faster time in order to reduce data fluctuations and provide higher productivity for the system than single VLC or RF networks. This was achieved by calculating the error location based on the triangulation equation and simulating data based on the received signal strength –triangulation and enhancing accuracy by implementing iterative, comprehensive and reinforcement learning methods. The network was localized in the internal environment by two stages. The first stage simulated the users location data using the triangulation method and entered the data into the deep learning algorithm. In the second stage, attention was paid to how to deal with noise, and the users location was accurately determined using RSS Triangulation. The thesis also focused on Load Balancing in order to ensure quality. According to the results, the system achieved a through put of up to 210 megabits per second SSS of 180 megabits per second . In addition, a user satisfactions rate of 100% was reported. Finally, on this occasion, we congratulate the student (Zeena Mustafa Ali) and wish her continued success.  

 The Department of Control and Systems Engineering held a workshop entitled (How to use the Bologna System) on Wednesday 11/9/2024 in the conference hall of the department. The workshop presented by the Director of the Registration unit (Assistant Lecturer Karam Samir Khaled), provided a comprehensive explanation of the Bologna system and the most important characteristics of this system that a faculty member need. The workshop also touched on details on how to deal with these characteristics and the main statistics that faculty members need, including knowing the number of subjects they are entrusted to teach, the number of students and required exams, the number of required hours, and the weekly schedule. By gaining knowledge of this information, the instructors can deal with student attendance to the system, add formative assessment and the mid-term marks, as well as understand the most important laws and regulations of the Bologna process.  

 The thesis of the master's student Dhiaa Shaltagh Shanan, specializing in Mechatronics Engineering, was discussed on Thursday, September 5, 2024, at Hall No. 9 in the Control and Systems Engineering Department. The research was entitled: Design and Implementation of different Control Strategies for Respiratory Systems The discussion committee consisted of: 1. Dr. Dhurgham Abdul Rahim Kazim / Chairman. 2. Dr. Alaa Abdel Hadi Jabr / Member. 3. Mina Qais Kazim / Member. 4. Dr. Salim Khalifa Kazim / Member and Supervisor. This study aims to ensure patient safety during the design of ventilators, as these medical devices assist patients in breathing. However, achieving optimal characteristics in opensource designs and conventional control loop mechanical ventilation units can be challenging. This study addresses this challenge by proposing robust controller formulations and comparing and analyzing the results of various control approaches for ventilation units. The study explores the effectiveness of conventional PID control, nonlinear PID control, and sliding mode control (SMC) using two signum functions as triggers for control actions when the sliding surface crosses a specific threshold. Each approach is evaluated and compared, considering the specific design of the ventilator and the application requirements. The fractional order SMC controller using the saturation method showed the highest improvement rate of 98%, achieving smoother control signals without overshoot (0.0165 mbar), a quick settling time (0.142 seconds), and no disturbances. By examining and analyzing the outcomes, this research aims to provide insights into the most suitable control approach for ensuring the safe and efficient operation of ventilators. The discussion was attended by Deputy Head of the Department for Scientific Affairs and Graduate Studies Dr. Abbas Hussein Issa. At the end of the discussion, the researcher was awarded a master’s degree with a grade of “excellent”, wishing the student Diaa Shaltagh Shanan continued success.  

 The master's thesis of the student (Lotfi Abdul-Kadhum Muhammad) specializing in (Computer Engineering) was discussed on Monday, 2/9/2024, in the discussion hall of the department. The thesis is entitled “Analysis and Comparison of Energy-Efficient Routing Algorithms” The discussion committee consisted of: 1- Asst. Prof. Dr. Dalal Abdul Mohsen Hmoud / Chairman 2- Asst. Prof. Farah Flaih Hassan / Member 3- Lect. Dr. Walid Fawaz Sharif / Member 4- Asst. Prof. Dr. Ahmed Mudher Hassan / Member and Supervisor 5- Asst. Prof. Dr. Ikhlas Kadhum Hamza / Member and Supervisor This thesis introduces two energy-efficient approaches for Wireless Sensor Networks (WSNs). The first approach improves the Ant Colony Optimization (ACO) algorithm by dynamically adjusting the alpha (α) and beta (β) parameters. This modification balances exploration and exploitation by altering how much pheromone trails and heuristic information influence the ants' decision-making process, improving energy-saving route selection. The second approach combines the Variable-length Genetic Algorithm (VLGA) with pruning and validation techniques to optimize paths for minimal energy consumption. Simulations are conducted using settings comprising 20, 50, 100, and 150 sensor nodes, and show that the proposed method outperforms traditional ACO in energy efficiency and achieves the same energy results as the Dijkstra algorithm. On this occasion, we congratulate the student (Lotfi Abdul-Kadhum Muhammad) and wish him continued success.